Author: Simon Jackson

A CEO we are working with asked me today about how large a deal she should look to do with an agricultural foundation that could become a big partner. As her company’s technology solves a major problem for them, she was aware that there was the potential to do a big initial deal but her instinct was to start small.

I think she was very right. We had a situation with another company for which we had opened a discussion with one of the largest surface materials companies in the world. We started by talking to one division, but other divisions within the company got wind of the technology and wanted to broaden the scope and raise the budget of the initial engagement.

Potentially very encouraging news, but as the scope widened, more stakeholders would be needed to approve the project and it would need to be synchronized with the work plans of more departments. What had been lined up as something relatively clean and straightforward was getting unwieldy and looking less and less likely to actually happen.

In the end, we were able to get back to the scope we had originally wanted ­– a modest project that could be both readily signed off and quickly executed. With the data generated from that first project, the internal champion we had nurtured within the company was in a much stronger position to set up larger projects for our client.

The lean approach to software creation has brought market testing much earlier in the life cycle of a product. Its aim is to try to find market acceptance as soon as possible so that companies minimise the risk of building products that turn out to be not sufficiently compelling.

How does this translate for non-software technology products?

If a product is based on new IP, it’s likely to have quite a long period before a first trial version is market ready. So how early should you start your commercialisation?

There is a concern that ramping up commercialisation efforts too far in advance of production readiness could lead to a loss of any momentum that has been built with potential customers and go-to-market partners. There is a temptation to think that it is better to put your head down and focus on getting to a production-ready model.

However, it’s important to remember that engaging the market serves a number of purposes:

There are often multiple parties that will be involved in the sales, implementation, operation and maintenance of a technology. Engaging with them is essential to understand what is required for each of them to adopt the technology. This will be central to the go-to-market strategy

Working with these parties will give a clearer sense of where the orders for the product will come from in the first 12 to 24 months post-launch. This is a period where sales velocity must be built. Only when they are prepared to shape up distribution or sales deals will it become clear that there is product-market fit. Confirming in advance where the actual orders are likely to come from will help mitigate commercial risk for investors and support valuation

Understanding why and how these parties will engage and buy is key to structuring a go-to-market strategy and sales process

In the process of verifying the needs of the market, it is quite possible that information will emerge that will result in changes to the product development path.

If market engagement is left too late, this information may not be uncovered. The cost of this in terms of lost time and missing targets will be considerable.

In his March 2014 budget the Chancellor announced that the Seed Enterprise Investment Scheme would become permanent.

This is the scheme that allows companies that have been trading for less than two years and that have less than £200,000 of assets to raise up to £150,000 of capital from UK investors with a tax treatment that makes it very attractive for the investors to invest.

For their part, investors can invest up to £100,000 per tax year spread across one or more companies.

How does it work?

UK tax-paying investors get a 50p tax credit on the monies that they invest as equity in SEIS-qualifying companies, regardless of the marginal income tax rate that they pay. Investors also receive capital gains tax relief of 50% on any capital gains they use to invest in SEIS-qualifying companies: for every £1 of capital gains invested, higher rate tax-paying investors get a 14p tax credit.

In the event that an investee business fails, the investor gets a further 22.5p in the pound tax write-off.

In summary what your recovery per pound invested is:

Tax Credit given

Company succeeds*

Company fails

Investor not investing capital gains

50%

72.5%

Investor investing capital gains

64%

86.5%

*providing the shares are held for 3 years or longer.

Plus, any capital gains made on the SEIS investments themselves are exempt from Capital Gains Tax.

Looking forward

While SEIS tax reliefs have only been available for investment in ordinary equity to date, the government is exploring whether similar reliefs can be extended to other investment instruments such as convertible loans.

SEIS is here to stay. Having an environment where entrepreneurs can de-risk equity investment for their early investors to such an extent is a big positive for innovation. While it means the Taxpayer will have to pick up the bill for the investments that will fail – and there will be many due to the nature of early stage investment – for those raising or investing money, the benefits are compelling.

There are many points in an entrepreneur’s journey where they will want to access specific, targeted guidance and experience beyond that of their employees, investors and professional advisors.

At RIG, we work with technology entrepreneurs to build the environments that will help them succeed, and this includes accessing strategically valuable external expertise.

There are a number of ways to do this. What comes into many people’s minds is going the Non-Executive Director route. While this can be done, the strategic advice that the entrepreneur needs can be separated from the fiduciary duties that go with being a director of a company. And in fact, many people that would volunteer to provide strategic advice would not want the responsibility of being a board member.

Our suggestion is to create an advisory panel. I say ‘panel’ rather than ‘board’ advisedly – in the research for our process, we spoke to many people who had set up advisory boards, and learned that in practice the word ‘Board’ can carry connotations, both internally and externally, of governance and decision-making responsibility.

The principal we follow is to design the best advisory panel that we can. Rather than working from who the entrepreneur knows, we work out what the objectives and requirements are and then find the best people we can to fill those roles.

Our starting point is to work with the entrepreneur to analyse the strategic needs and weaknesses of her company. By setting this against the vision of where she wants the company to get to, we can identify the areas where external advisors can add the most value. Some of these areas will be appropriate for an advisory panel to address, while some – such as coaching of senior management – are better kept out of scope and addressed by other means.

This analysis also prepares the ground for articulating a set of objectives to be given to the advisory panel. This shapes what the panel members will be asked to work on and what will be expected of them.

With the objectives clearly understood, the next step is to identify the ‘required’ versus ‘desired’ skills and experience for panel members. Knowing what these are, it is possible to think about where we might find the right people.

It’s important to remember that in building the panel, we are looking people not only with the right kind of experience; they will need to be able to identify with the entrepreneur and the journey that they are taking.

How large should an advisory panel be? It’s a trade-off between being large enough to provide a breadth of input, and small enough that all of the members are very involved. We have found that a panel of three or four is a good size to work with.

Knowing how many people you will have, it is then a question of finding the required mix of skills and experience. No one will have all the elements of experience, but the group should do overall. Importantly, they should work together well as a group, and this will be an important factor in determining which people are ultimately selected from the shortlist.

It’s not a surprise that CEOs of early-stage companies can have little regard for financial models. Possibly made by someone not full-time in their business, the financial model is viewed as being of limited value in decision-making; as something that is created predominantly to satisfy investors.

Business models for early-stage companies that I have seen frequently have one or more of the following characteristics:

It’s not easy to see what the key assumptions and drivers underpinning the business model are

Costs and revenues are not linked, which means you can’t see what happens to the business if the revenue assumptions are changed

They fudge the answer to ‘but when do we get the money?’

They are not at all easy to read through

They’re over-elaborate: there’s too much conjectural detail relating to revenue streams that might happen some time in the future

Above all, I see models that are not aligned to the business narrative and objectives. It is no wonder that management don’t feel like their models are relevant in how they understand their own business.

So what then should a good model for an early stage business be/do?

Much is uncertain in an early-stage business. To quote Steve Blank, ‘the primary objective of a startup is to validate its business model hypotheses’ – i.e. they are just that, hypotheses. Yet it can feel to CEOs like they have to depict certainty in a financial model in order to give investors assurance.

An early stage business model should contain just enough detail to represent the central cash-generating dynamics and dependencies of the business.

At a minimum (and probably a maximum!), the model should set down and link:

What the key revenue and cost drivers are for the business

What needs to be true for the business to succeed – i.e. the key assumptions

What determines the timing of money into and out of the business

If the model does this, then it can help the management to understand the relative magnitude of the different drivers and assumptions on the development of business, see what scale they need to be as cash-generative as they aspire to be, and understand how long their cash runway is.

Above all, a financial model should mirror the way that management describes its business and objectives and better enable the management to articulate – for both internal and external consumption – the flow of their business model.

In my next post, I will start to set out some fundamental steps for building such a model.

Sometimes you may be lucky and/or smart enough to see a big commercial trend coming well ahead of the pack. It can be likened to being on a surfboard and seeing a sizeable wave coming: you then try and get into just the right position for when the wave arrives.

Sometimes the size of the impending wave can make you think that there you will make money just by being in the right place. However, if the opportunity is large and you’re really going to catch and ride it, there are two important high-level decisions worth making:

What minimum scale do you need to build in order to capitalise on the opportunity? and

Which part of the wave both offers profitable growth and the opportunity to build a protectable position?

Scale is important because if your surfboard is too small when the wave hits, you will either not be able to service the nascent market need well enough, or you will not be able to build a sustainable position. You then risk rapidly becoming irrelevant.

Finding the right area of the wave is important because a major opportunity will attract many new entrants and, unless the ability to compete requires highly-differentiated capabilities which only you have, you shouldn’t kid yourself about the extent of the barriers to entry.

As an example, I was involved in building a cross-border mergers & acquisitions business between India and the rest of the world in the early 2000s. We had predicted that Indian companies would start to make overseas acquisitions and that there would be a need for good quality advisory services. Our assumptions turned out to be true: an initial trickle of small overseas acquisitions by Indian buyers turned into a flood of deals (including Tata-Jaguar Land Rover, Tata-Corus). We executed some high profile deals early on and established a reputation for the quality of our execution.

Our buy-side-focused proposition was exactly right for the early stage of development of the market. But barriers to entry into this market for other advisory firms were low and our lack of scale became an issue once the bulk of the wave hit. Ultimately, our company reoriented into a more defendable niche within the growing India story, but we would have benefited from an earlier analysis of the relationship between minimum scale and sustainable value capture.

The cry sounds very familiar: “Big Data. We’re doing Big Data”. Substitute ‘the Internet” for “Big Data” and it could be 1997.

In 1997, it was very common to meet people who were “doing the Internet”. It was by far the most exciting game in town. There was often not so much understanding of how “doing the Internet” was going to generate value. There were new business models and new future titans being built. It was also imperative for all existing big corporates to be doing it. They didn’t have the in-house skills, so a raft of product and service start-ups mushroomed to fill the as-yet-not-so-defined gap.

There is a similar rush now with Big Data. And as in the internet rush, while there are some people that are building and investing in companies that generate and look set to monetise Big Data, there are also many that are looking to take advantage of and fill the gap that the lack of maturity in this discipline has opened up. In many cases, it’s not obvious what kind of business is actually being created.

In a way, this is to be expected. As in the early days of any emergent field, there is a surge of new entrants. This is particularly helped by the fact that much of the underlying technology that is being used to manipulate Big Data is open source. The cost of participating is low, while the perceived need is great.

When looking at companies that want to provide services to enterprises, one major decision is between whether to offer a platform or an industry-specific solution. At RIG, we have come across quite a lot of companies that are in the middle – they have a basic platform that they are trying to use to solve problems for a range of customers. Essentially they are offering tool-driven consultancy, taking advantage of the gap – as for the internet – where core mass data handling skills are not yet embedded in the organisations that have the data and which are facing the expectation of being able to do something interesting with it.

This can be a starting point, but we would strongly recommend that they quickly move to focus on a cohesive set of industry-specific problems, preferably for an industry whose problems they understand well. As my colleague David Gates’ wrote in his recent blog post, having market focus sharpens a company, improves its product, and ultimately allows it to offer and extract more value.

Sometimes early success can get in the way of finding a better path of evolution. One company we spent time with had won a couple of big name customers, but was having to spend a huge amount of time providing consulting and customisation services to deliver. The business plan showed a move to a self-serve product and ramping sales numbers, but it seemed that much of their value was actually in their ability to consult.

Ultimately, Big Data will go the same way as the internet. It will spawn a host of new technologies and tools. It will become a core competence for most large corporates; there will be some excellent ‘pure Big Data’ companies. And it will create a raft of new kinds of jobs. While we should expect that most of the current Big Data startups will not last, their existence now is important as part of launching the movement to imagine and unlock the value of data.

Hats off to Mike Butcher: he runs a great event. London Web Summit, held yesterday at The Brewery, this time brought together with Paddy Cosgrave of Dublin Web Summit, drew a wide range of entrepreneurs, investors and ‘glue’ people in a day packed full with panels, interviews, discussions and startup presentations. There was a ‘coding dojo’ for kids. There was even a band, just like on The Tonight Show. The networking was excellent – there was a matching platform for surfing the delegates and booking meetings in advance. In terms of rallying the startup ecosystem, to quote the song, “nobody does it better”…

Content-wise, there was lots on cool new ideas, and, as ever, much focus on getting VC funding and whether there is enough of it, and a session on exits. I couldn’t help feeling though that the bit in the middle – i.e. building and scaling the business – was completely glossed over. Finding out from practitioners the answers to questions like “How are you changing your organisation as it grows?”, “How have you created a scalable model and what did you need to learn before you were ready to scale?” and “How are you structuring your sales and marketing efforts to ensure you deliver your growth milestones?” can only be instructive and thought-provoking to anyone going on the same journey.

There was a fair amount of attention given to hiring the right people, but the implicit assumption is that if you get the right people, then all of this will be taken care of. If exactly the right people exist, then maybe it will be, but in practice, very few people have all the right skills, and even then, there is so much that can be learned.

With Sonali de Rycker of Accel Partners saying that it is normal for up to 8 out of 10 of their investments to fail, the odds of success post-funding are still only 1 in 5, which means that getting funding is only the start of the journey (even with a world-class VC). In this case, why would you not want to devote a huge amount of time to learning about how to navigate the course and mitigate the risk?

Quite possibly it’s not the point of an event like this to look at how to generate and manage growth. Perhaps it’s felt that it wouldn’t make for an interesting discussion – maybe it’s too detailed and too specific. But if not here, then where?

RIG recently hosted a CEO roundtable dinner to explore what it takes to make a board work.

The discussion revealed that only one of the CEOs had ever had a board that had functioned well and pushed the company forward. Overall the level of dissatisfaction with boards was high.

The main sources of dissatisfaction for the CEOs present were:

Not having a board that could contribute or challenge them sufficiently on strategic issues‬

Particularly for first time entrepreneurs, having a board made up mainly of executives/founders, making it difficult to switch out of operational mode into a more strategic mindset‬

Finding that board meetings had become reporting sessions to professional investors. While the financial rigour of professional investors was valued, it tended to take precedence over strategic discussion and the investors often expected to be treated as first among equals‬

So what kind of capabilities and composition would they like to have (or have had) for their boards?

At early stage, people with contacts – essentially high-level salespeople or door-openers‬

Closer to exit, a board that can spot and generate exit opportunities‬

At all times: people who have done it before – who can challenge and whose experience can be leaned on.

‬There was much lamentation in particular at the lack of sales experience among virtually all the boards – it was felt by all that this is an essential part of the balance that is generally missing.

Above all, there was agreement that a board has to have a clear purpose that fits with the needs of the company at its stage of development. Because the early stage environment is one of change, the composition of the board may need to change more regularly than would be the case for a more mature company.

How then to put together a board that is a good fit?

‪Understand the needs of the company at each stage – this should determine the purpose of the board

Hackathons are generally seen as being the preserve of enthusiastic developers. It’s all about the code, surely..??

I recently had the good fortune to be accepted for the Seedcamp Seedhack event – there were going to be 120 attendees, with a mix between coders and ‘business types’. My personal aim in going was to see inside the black box and understand what ‘bits’ it actually takes to build a web app/service.

As the event approached, I had a sense of great excitement at taking part but also a lot of self-doubt: what can I possibly contribute?

Shortly after arriving at LBS on a Friday evening, we were taken at breakneck pace through a raft of API presentations by companies such as Facebook and GIS Cloud. Then there was a special session highlighting the role that entrepreneur-driven innovation can play in the delivery of healthcare: Richard Stubbs, Programme Director for NHS Innovation Challenge Prizes, hailed the role of local initiatives as the antidote to the ‘one big system mentality’ behind the failed NHS core IT project. This was then nicely illustrated by the presentation that Mohammed Al-Ubaydli gave on the approach that his company, Patients Know Best, takes to healthcare data innovation.

In the days running up to the event, we had all been encouraged to post ideas on the event’s forum so that they could be commented on and voted on. The people with the highest scoring ideas then pitched them to the room – ideas included a credit scoring system based on social media data, a Facebook API-driven social dating application and an online social calendar. Teams were formed on the spot and went off to start work. Our mission was to have a minimum viable product (i.e. a working demonstration) by 4pm on Sunday.

Although I had posted my own idea which was a concept based on emerging Smart TV platforms, I chose instead to join an existing group so I could see a web app being built from the ground up. I joined up with three bright young developers from a development company in Bielsko-Biala, Poland who wanted to write a web-delivered system to integrate all the different operating and financial data sources that a small professional services company uses in order to generate easy and insightful profitability analysis metrics.

Fortunately I was able to be very useful – there was an emphasis on having an outline business rationale (which was based on the Lean Canvas framework) – so ‘business types’ like me were able to provide critical input on the customer proposition, the routes to market and the revenue models.

What was great was how much the developers valued the business input as they wanted to make something not just ‘cool’ but also with commercial potential.

By Sunday, most of the teams had a product demonstration ready. My team had a nicely designed online dashboard with a set of metrics and interactive Javascript graphs linked to dummy data on a custom-built Ruby on Rails engine. Very satisfying!

As we headed off to the nearby pub, everyone was happy but exhausted – at least one person had coded for 48 hours straight! I came out of the event with a much better sense of what it takes to build a decent web service, and having met a really good bunch of talented and motivated people (and having eaten more pizza in two days than I thought was humanly possible).

If you haven’t attended a hackathon, I would strongly recommend it!

Many thanks to Carlos Eduardo Espinal of Seedcamp and his team for putting together a fantastic event.